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I’ve just had a really interesting first day at TM Forum’s Digital Transformation Asia (https://dta.tmforum.org and #tmfdigitalasia ). The quality of presentations was quite high. Some great thought-provoking ideas!!

Nik Willetts kicked off his keynote with the following quote, which I’m paraphrasing, “Telcos need to start capturing value, not just creating it as they have for the last decade.”

For me, this is THE key takeaway for this event, above any of the other interesting technical discussions from day 1 (and undoubtedly on the agenda for the next 2 days too).

The telecommunications industry has made a massive contribution to the digital lifestyle that we now enjoy. It has been instrumental in adding enormous value to our lives and our economy. But all the while, telecommunications providers globally have been experiencing diminishing profitability and share-of-wallet (as described in this earlier post). Clearly the industry has created enormous value, but hasn’t captured as much as it would’ve liked.

The question to ask is how will our thinking and our OSS/BSS stacks help to contribute to capturing more value for our customers. As described in the share of wallet post above, the premium end of the value chain has always been in the content (think in terms of phone conversations in days gone by, or the myriad of comms techniques today such as email, live chat, blogs, etc, etc). That’s what the customer pays for – the experience – not the networks or systems that facilitate it.

The Internet has allowed enormous proliferation of the premium-end of the telecommunications value chain. It’s too late to stuff that genie back into the bottle. But to Nik’s further comment, we can help customers achieve their goals by becoming their “do-it-yourself” digital partners.

In OSS there are some tasks that require availability (the green button on communicator). The Network Operations Centre (NOC) is one. But does it require on-site presence in the NOC?

An earlier post showed how wrong I was about collaboration rooms. It seems that ticket flicking (and perhaps communication tools like slack) is the preferred model. If this is the preferred model, then perhaps there is no need for a NOC… perhaps only a DR NOC (Disaster Recover NOC).

“Truth is, there are hardly any good reasons to know if someone’s available or away at any given moment. If you truly need something from someone, ask them. If they respond, then you have what you needed. If they don’t, it’s not because they’re ignoring you – it’s because they’re busy. Respect that! Assume people are focused on their own work.Are there exceptions? Of course. It might be good to know who’s around in a true emergency, but 1% occasions like that shouldn’t drive policy 99% of the time. ”Jason Fried on Signal v Noise

The one area where I’m considering the paradox of presence is in OSS design / architecture. There are often many facets of a design that require multiple SMEs – OSS application, security, database, workflow, user-experience design, operations, IT, cloud etc.

When we get many clever SMEs in the one room, they often have so many ideas and so much expertise that the design process resembles an endless loop. Presence seems to inspire omnipresence (the need to show expertise across all facets of the design). Sometimes we achieve a lot in these design workshops. Sometimes we go around in circles almost entirely because of the cleverness of our experts. They come up with so many good ideas we end up in paralysis by analysis.

The idea I’m toying with is how to use the divide and conquer theory – being able to carve up areas of responsibility and demarcation points to ensure each expert focuses on their area of responsibility. Having one expert come up with their best model within their black box of responsibility and connecting their black box with adjacent demarcation points. The benefits are also the detriments. The true double-edged sword. The benefits are having one true expert work through the options within the black box. The detriments are having only one expert work through the options within the black box.

There are some past projects that I wished I’d tried to inspire the divide and conquer approach in hindsight. In others, the collaboration model has worked extremely well.

But to get back to presence, I wonder whether thrashing up front to define black boxes and demarcation points then allows the experts to do their thing remotely and become less inclined to analyse and opine on everyone else’s areas of expertise.

* I use the term staff to represent anyone representing the organisation (staff, contractor, consultant, freelancer, etc)

The project team is disconnected from the users – The team that’s building the OSS in parallel to existing operations doesn’t (or isn’t able to) engage with the end users of the OSS. Once it comes time for cut-over, the end users want to stick with what they know and don’t use the shiny new OSS. From painful experience I can attest that stakeholder management is under-utilised on large OSS projects.

Turf wars – Different groups within a customer are unable to gain consensus on the solution. For example, the operational design team gains the budget to build an OSS but the network assurance team doesn’t endorse this decision. The assurance team then decides not to endorse or support the OSS that is designed and built by the design team. I’ve seen an OSS worth tens of millions of dollars turned off less than 2 years after handover because of turf wars. Stakeholder management again, although this could be easier said than done in this situation.

It sounded like a good idea at the time – The very clever OSS solution team keeps coming up with great enhancements that don’t get used, for whatever reason (eg non fit-for-purpose, lack of awareness of its existence by users, lack of training, etc). I’ve seen a customer that introduced over 500 customisations to an off-the-shelf solution, yet hundreds of those customisations hadn’t been touched by users within a full year prior to doing a utilisation analysis. That’s right, not even used once in the preceding 12 months. Some made sense because they were once-off tools (eg custom migration activities), but many didn’t.

The new OSS is a scary beast – The new solution might be perfect for what the customer has requested in terms of functionality. But if the solution differs greatly from what the operators are used to, it can be too intimidating to be used. A two-week classroom-based training course at the end of an OSS build doesn’t provide sufficient learning to take up all the nuances of the new system like the operators have developed with the old solution. Each significant new OSS needs an apprenticeship, not just a short-course.

It’s obsolete before it’s finished – OSS work in an environment of rapid change – networks, IT infrastructure, organisation models, processes, product offerings, regulatory shifts, disruptive innovation, etc, etc. The longer an OSS takes to implement, the greater the likelihood of obsolescence. All the more reason for designing for incremental delivery of business value rather than big-bang delivery.

What other examples have you experienced where an OSS has been built, but the users haven’t come?

There’s a common belief that most jobs see people rewarded for presence rather than performance. That is, they’re encouraged to be on site from 9am to 5pm rather than being given free reign over their work schedules as long as key outcomes are met / exceeded.

In OSS vendor / product selection there’s a similar concept. Contracts are often awarded based on existence rather than excellence. When evaluating a product, if it’s able to do a majority of the functions in the long list of requirements then the box is ticked.

However, this doesn’t take into account that there are usually only a very small number of functions that any given customer’s OSS needs to perform at a very high level of efficiency. All the others are effectively just nice to have. That’s the 80/20 rule at work.

When guiding a customer through their vendor selections, I always take them through an exercise to identify the use-cases / functions that really matter. Then we ensure that the demos or proofs of concept focus closely on how excellent the OSS is at those most important factors.

Automation is about using machines / algorithms to respond faster than humans can, or more efficiently than humans can, or more accurately than humans can… but only if the outcomes justify the costs. When it comes to automations, it’s a case of, “just because we can, doesn’t mean we should.”

The more complex the decision tree you’re trying to automate, the higher the costs and therefore the harder it becomes to cost-justify. So the first step in any automation is taking a lateral thinking approach to simplifying the decision tree.

This recent post highlighted a graph from Nokia’s Bell Labs and the financial dependency that network slicing has on operational automation:

Let’s use the Toyota Five Whys technique to work our way through the implications of this:

Statement 0: As CSPs, we need to drastically reduce complexity in the processes / decision-trees across our whole organisation.

Why 1? So that we can apply significant levels of automation

Why 2? So that we can apply technologies / techniques such as network slicing or virtualisation that are cost-justifiable

Why 3? So that we can offer differentiated, premium services

Why 4? So that our offerings don’t become commodities

Why 5? So that we retain corporate profitability to return to shareholders and/or invest in further interesting projects

I love that we’re looking to all number of automation technologies / techniques to apply to our OSS. However, we’re bypassing the all-important statement 0. We’re starting at Why 1 and partially missing the cost-justifiable part of Why 2. If our automation projects don’t prove cost-justifiable, then we never get the chance to reach whys 3, 4 and 5.

“Network slicing opens new business opportunities for operators by enabling them to provide specialized services that deliver specific performance parameters. Guaranteeing stringent KPIs enables operators to charge premium rates to customers that value such performance. The flip side is that such agreements will inevitably come with tough contractual obligations and penalties when the agreed KPIs are not met…even high numbers of slices could be managed without needing to increase the number of operational staff. The more automation applied, the lower the operating costs. At 100 percent automation, there is virtually no cost increase with the number of slices. Granted this is a long-term goal and impractical in the short to medium term, yet even 50 percent automation will bring very significant benefits.”
From a paper by Nokia – “Unleashing the economic potential of network slicing.”

These custom requirements often come with unique network configuration requirements. This is why network slicing has become an attractive proposition. The white paper quoted above makes an attempt at estimating profitability of network slicing including some sensitivity analyses. It makes for an interesting read.

The diagram below is one of many contained in the White Paper:

It indicates that a significant level of automation is going to be required to achieve an equivalent level of operational cost to a single network. To re-state the quote, “The more automation applied, the lower the operating costs. At 100 percent automation, there is virtually no cost increase with the number of slices. Granted this is a long-term goal and impractical in the short to medium term, yet even 50 percent automation will bring very significant benefits.”

Even 50% operational automation is a significant ambition. OSS hold the key to delivering on this ambition. Such ambitious automation goals means we have to look at massive simplification of operational variant trees. Simplifications that include, but go far beyond OSS, BSS and networks. This implies whole-stack simplification.

“The iPhone disrupted the handset business, but has not disrupted the cellular network operators at all, though many people were convinced that it would. For all that’s changed, the same companies still have the same business model and the same customers that they did in 2006. Online flight booking doesn’t disrupt airlines much, but it was hugely disruptive to travel agents. Online booking (for the sake of argument) was sustaining innovation for airlines and disruptive innovation for travel agents.
Meanwhile, the people who are first to bring the disruption to market may not be the people who end up benefiting from it, and indeed the people who win from the disruption may actually be doing something different – they may be in a different part of the value chain. Apple pioneered PCs but lost the PC market, and the big winners were not even other PC companies. Rather, most of the profits went to Microsoft and Intel, which both operated at different layers of the stack. PCs themselves became a low-margin commodity with fierce competition, but PC CPUs and operating systems (and productivity software) turned out to have very strong winner-takes-all effects.”
Ben Evans on his blog about Tesla.

As usual, Ben makes some thought-provoking points. The ones above have coaxed me into thinking about OSS from a slightly perspective.

I’d tended to look at OSS as a product to be consumed by network operators (and further downstream by the customers of those network operators). I figured that if our OSS delivered benefit to the downstream customers, the network operators would thrive and would therefore be prepared to invest more into OSS projects. In a way, it’s a bit like a sell-through model.

But the ideas above give some alternatives for OSS providers to reduce dependence on network operator budgets.

Traditional OSS fit within a value-chain that’s driven by customers that wish to communicate. In the past, the telephone network was perceived as the most valuable part of that value-chain. These days, digitisation and competition has meant that the perceived value of the network has dropped to being a low-margin commodity in most cases. We’re generally not prepared to pay a premium for a network service. The Microsofts and Intels of the communications value-chain is far more diverse. It’s the Googles, Facebooks, Instagrams, YouTubes, etc that are perceived to deliver most value to end customers today.

If I were looking for a disruptive OSS business model, I wouldn’t be looking to add exciting new features within the existing OSS model. In fact, I’d be looking to avoid our current revenue dependence on network operators (ie the commoditising aspects of the communications value-chain). Instead I’d be looking for ways to contribute to the most valuable aspects of the chain (eg apps, content, etc). Or even better, to engineer a more exceptional comms value-chain than we enjoy today, with an entirely new type of OSS.

When selecting new applications for an OSS or to augment an existing OSS, it always makes sense to me to run a Proof of Concept. But what do we want to demonstrate in that PoC? For me, we want to run demonstrations of the factors (eg features, use-cases, processes, etc) that justify the investment.

A simple exercise you can use is to identify the personas / roles that interact with the OSS. This could include personas such as NOC operator, strategic planner, network engineer, order entry, field ops, data / analytics, application administrator, etc. The actual personas will differ within each organisation of course.

For each of those personas, we can identify and interview an individual that represents that persona.

Interview questions include:

What are the key responsibilities of your role

What is the most important goal / KPI for your role

How does this OSS (or proposed OSS) support you meeting this goal

Describe the single most important process / function that you perform using the OSS

Why is it so important

How often do you perform this process / function

Please provide a short list of other important processes / functions you perform with this OSS

We can then build this into a matrix and seek to prioritise into a set of use-cases. Based on time and cost constraints, we can then build the top-n of those use-cases into implementation scenarios for the PoC.

Like this:

I was lucky enough to get some time of a friend recently, a friend who’s running a machine-learning network assurance proof-of-concept (PoC).

He’s been really impressed with the results coming out of the PoC. However, one of the really interesting factors he’s been finding is how frequently BAU (business as usual) changes in the OSS data (eg changes in naming conventions, topologies, etc) would impact results. Little changes made by upstream systems effectively invalidated baselines identified by the machine-learning engines to key in on. Those little changes meant the engine had to re-baseline / re-learn to build back up to previous insight levels. Or to avoid invalidating the baseline, it would require re-normalising all of data prior to the identification of BAU changes.

That got me wondering whether DevOps (or any other high-change environment) might actually hinder our attempts to get machine-led assurance optimisation. But more to the point, does constant change (at all levels of a telco business) hold us back from reaching our aim of closed-loop / zero-touch assurance?

Just like the proverbial self-driving car, will we always need someone at the wheel of our OSS just in case a situation arises that the machines hasn’t seen before and/or can’t handle? How far into the future will it be before we have enough trust to take our hands off the OSS wheel and let the machines drive closed-loop processes without observation by us?

Is it just me or has there been a proliferation of superhero movies coming out at cinemas lately? Not only that, but movies where teams of superheros link up to defeat the baddies (eg Deadpool 2, Justice League, etc)?

The thing that strikes me as interesting is that there’s rarely an overlap of super-powers within the team. They all have their different strengths and points of difference. The sum of the parts… blah, blah, blah.

Anyway, I’m curious whether you’ve noticed the same thing as me on OSS projects, that when there are multiple team members with significant skill / experience overlap, the project can bog down in indecision? I’ve noticed this particularly when there are many architects, often super-talented ones, on a project. Instead of getting the benefit of collaboration of great minds, we can end up with too many possibilities (and possibly egos) to work through and the project stagnates.

If you were to hand-pick your all-star cast for your OSS Justice League, just like in the movies, you’d look for a team of differentiated, but hopefully complementary, super-heroes I assume. But I’m diverting away from my main point here.

Each project, just like each formidable foe in the movies, is slightly different and needs slightly different super-powers to tackle it. When selecting a cast for a movie, directors have a global pool to choose from. When selecting a cast for an OSS project, directors have traditionally chosen from their own organisation, possibly with some outside hires to fill the long-term gaps.

With the increasing availability of freelance resources (ie people who aren’t intrinsically tied to carriers or vendors), the proposition of selecting a purpose-built project team of OSS super-heroes is actually beginning to become more possible. I’m wondering how much the gig economy will change the traditional OSS project team model in coming years.

In other industries, we hear of buying groups getting great deals through aggregated buying volumes. This is a little harder to achieve with products that are as uniquely customised as OSS. It’s possible that OSS buy-side aggregation could occur for operators that are similar in nature but don’t compete (eg regional operators). Having said that, I’ve yet to see any co-ops formed to gain OSS group-purchase benefits. If you have, I’d love to hear about it.

In OSS, there are three approaches that aren’t exactly co-op buying models but do aggregate the evaluation and buying decision.

A far less formal co-op buying model I’ve noticed is the social-proof approach. This is where one, typically large, network operator in a region goes through an extensive OSS / BSS evaluation and chooses a vendor. Then there’s a domino effect where other, typically smaller, network operators also buy from the same vendor.

Even less formal again is by using third-party organisations like Passionate About OSS to assist with a standard vendor selection methodology. The vendors selected aren’t standardised because each operator’s needs are different, but the product / vendor selection methodology builds on the learnings of past selection processes across multiple operators. The benefits comes in the evaluation and decision frameworks.

I’d like to get your opinion on this question – are OSS business tools or technical tools?

We can say that BSS are as the name implies – business support systems.
We can say that NMS / EMS / NEMS are network management tools – technical tools.

The OSS layer fits between those two layers . It’s where the business and technology worlds combine (collide??).

If we use the word Operations / Operational to represent the “O” in OSS, it might imply that they exist to help operate technology. Many people in the industry undoubtedly see OSS as technical, operational tools. If I look back to when I first started on OSS, I probably had this same perception – I primarily faced the OSS / NMS interface in the early days.

But change the “O” to operationalisation and it changes the perspective slightly. It encourages you to see that the technology / network is the means via which business models can be implemented. It’s our OSS that allow operationalisation to happen.

They’re both right? And therefore as OSS operators / developers / implementers, we need to expand our vision of what OSS do and who they service… which helps us get to Simon Sinek’s Why for OSS.

OSS of the past probably tended to be the point of collision and friction between business and tech groups within an organisation. Some modern OSS architectures give me the impression of being meet-in-the-middle tools, which will hopefully bring more collaboration between fiefdoms. Time will tell.

Like this:

How many OSS business cases have you seen that are built around cost reduction? Most of them??

Now let me ask the same question, but with one extra word included and see whether it completely inverts your answer. How many OSS business cases have you seen that are built on capital cost reduction? None of them?? Almost every “cost-out” business case is built on operational cost reduction (eg head-count reduction) – OPEX, not CAPEX – right?

So, you may ask, what does a CAPEX-reduction business case get built around? The benefits tend to be a little more obscure, but let’s see if they might work for you.

The first is probably also the most obvious – speed and cost of deployment. Not of the OSS itself, but all of the projects and micro-projects that the OSS helps to manage. If your OSS can systematically reduce deployment time and/or cost, then you get significant cost out

Asset utilisation – if you can find better ways to spread the load across your assets, then there’s less to spend on asset augmentation

Asset identification – you might be surprised at how many assets go missing and not necessarily through pilfering. I advised on a project where the payback period on a complete OSS was only a couple of months because the customer found a few very expensive pieces of equipment that were purchased, tested, physically connected (and having maintenance paid on) but never had services activated through them. The customer was just about to order a few more of the same devices to augment the network, but didn’t need to (a slightly different example of #2 above)

Cost justification of assets – to use historical and projected information to optimise new build (ie equipment purchase, deployment time, etc)

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NPS, or Net Promoter Score, has become commonly used in the telecoms industry in recent years. In effect, it is a metric that measures friction in the business. If NPS is high, the business runs more smoothly. Customers are happy with the service and want to buy more of it. They’re happy with the service so they don’t need to contact the business. If NPS is low, it’s harder to make sales and there’s the additional cost of time dealing with customer complaints, etc (until the customer goes away of course).

NPS can be easy to measure via survey, but a little more challenging as a near-real-time metric. What if we used customer contacts (via all channels such as phone, IVR, email, website, live-chat, etc) as a measure of friction? But more importantly, how does any of this relate to OSS / BSS? We’ll get to that shortly (I hope).

BSS (billing, customer relationship management, etc) and OSS (service health, network performance, etc) tend to be the final touchpoints of a workflow before reaching a customer. When the millions of workflows through a carrier are completing without customer contact, then friction is low. When there are problems, calls go up and friction / inefficiency is also going up. When there are problems, the people (or systems) dealing with the calls (eg contact centre operators) tend to start with OSS / BSS tools and then work their way back up the funnel to identify the cause of friction and attempt to resolve it.

The problem is that the OSS / BSS tools are often seen as the culprit because that’s where the issue first becomes apparent. It’s easier to log an issue against the OSS than to keep tracking back to the real source of the problem. Many times, it’s a case of shooting the messenger. Not only that, but if we’re not actually identifying the source of the problem then it becomes systemic (ie the poor customer experience perpetuates).

Maybe there’s a case for us to get better at tracking the friction caused further upstream of our OSS / BSS and to give more granular investigative tools to the call takers. Even if we do, our OSS / BSS are still the ones delivering the message.

Like this:

Can you guess what automated OSS testing and OSS new starters have in common?

Both are best front-loaded.

As a consultant, I’ve been a new starter on many occasions, as well as being assigned new starters on probably even more occasions. From both sides of that fence, it’s far more effective to front-load the new starter with training / knowledge to bring them up to speed / effectiveness, as soon as possible. Far more useful from the perspective of quality, re-work, self-sufficiency, etc.

Unfortunately, this is easier said than done. For a start, new starters are generally only required because the existing team is completely busy. So busy that it’s really hard to drop everything to make time to deliver up-front training. It reminds me of this diagram.

Front-loading of automated testing is similar… it takes lots of time to get it operational, but once in place it allows the team to focus on business outcomes faster.

In both cases, front-loading leads to a decrease in efficiency over the first few days, but tends to justify the effort soon thereafter. What other examples of front-loading can you think of in OSS?

Like this:

“CSPs’ needs in orchestration are evolving in parallel on several dimensions. These can be considered hierarchically. At the highest level is software that has an end-to-end service role, as is the case in the ONAP project. This software generally supports a service life-cycle perspective, containing functions from design and service creation, to provisioning and activation, to operations management, analysis, upgrade and evolution.
Beneath this tier, in a resource-facing sense, is software that simplifies deployment and operation of virtual system infrastructures in cloud-native applications, NFV, vco/CORD and MEC. This carries the overall tag of MANO and incorporates the domains of NFV (with NFVO, for deployment and operation of virtualized network functions) and virtualized infrastructure management (or VIM, for automating deployment and operation of virtual system infrastructures). Open source developments are significant at each of these layers of orchestration, and each contains a significant portion of the overall orchestration TAM.
In parallel is the functionality for managing hybrid virtual and physical infrastructures, which is the reality in most CSP environments. This can be thought of as a lateral branch to MANO for virtualized infrastructures in the orchestration stack.
Together these categories make up the TAM [Total Addressable Market] for orchestration solutions with CSPs. This is a high-priority area of focus for CSPs and is one of the highest growth areas of software innovation and development in support of their service delivery needs. We expect the TAM for orchestration software to triple from 2018 through 2023 at a CAGR of 32.5%. This is partially because of the nascent level of the offerings at the current time, as well as the high priority that CSPs and their vendor suppliers are placing on the domain.”
“Succeeding on an Open Field: The Impact of Open Source Technologies on the Communication Service Provider Ecosystem,” an ACG Research Report.

Whilst the title of this blog is just one of the headline numbers in this report by ACG Research, there are a number of other interesting call-outs, so it’s well worth having a closer read of the report.

The research has been funded by the Linux Foundation, so it naturally has a focus on open-source solutions for network operators (CSPs). Here’s another quote from the report relating to open-source, “The main motivations behind the push for open source solutions in CSP operations are not simply focused on cost reduction as a goal. CSPs are thinking strategically and globally. There is a realization that the competitive landscape for communication and information services is changing rapidly, and it includes global, webscale service providers and over-the-top solutions.
Leading CSPs want industry collaboration and cooperation to solve common challenges…
Their top three motivations are:
• Unifying multiple service providers around a common approach
• Avoiding vendor lock-in and dependencies on a single vendor
• Accessing a broader talent pool than your own organization or any one vendor could provide”

The first bullet-point is where the CSPs diverge from the likes of AWS and Google. Whilst the CSPs, each with their local geographical reach, seek global unification through standardisation (ie to ensure simpler interconnection), AWS and Google appear to be seeking global reach and global domination (making unification efforts irrelevant for them).

Just curious though. What if global domination does come to pass in the next few years? Will there be a three-fold increase in the orchestration market or complete decimation? Check out this earlier post that describes an OSS doomsday scenario.

Global CSPs have significant revenue streams that won’t disappear by 2023 and will be certain to put up a fight against becoming obsolescent under that doomsday scenario. It seems that open source and orchestration are key weapons in this global battle, so we’re bound to see some big investments in this space.

Like this:

“Insurer IAG has modelled the financial cost that a data breach or ransomware attack would have on its business, in part to understand how much proposed infosec investments might offset its losses.
Head of cybersecurity and governance Ian Cameron told IBM Think 2018 in Sydney that the “value-at-risk modelling” project called upon the company’s actuarial expertise to put numbers on different types and levels of security threats.
“Because we’re an insurance company, we can use actuarial methods to price or model what the costs of a loss event would be,” Cameron said.
“If we have a major data breach or a major ransomware attack, we’ve done some really great work in the past 12 months to model the net cost of losses to our organisation in terms of the loss of productivity, the cost of advertising to address the concerns of our customers, the legal costs, and the costs of regulatory oversight.
“We’ve been able to work out the distribution of loss from a small event to a very big event.”
Ry Crozier on IT News.

There are really only three main categories of benefit that an OSS can be built around:

Cost reduction

Revenue generation / increase

Brand value (ie insurance of the brand, via protection of customer perception of the brand)

The last on the list is rarely used (in my experience) to justify OSS/BSS investment. The IAG experience of costing out infosec risk to operations and brand is an interesting one. It’s also one that has some strong parallels for the OSS/BSS of network operators.

Many people in the telecoms industry treat OSS/BSS as an afterthought and/or an expensive cost centre. Those people fail to recognise that the OSS/BSS are the operationalisation engines that allow customers to use the network assets.

Just as IAG was able to do through actuarial analysis, a telco’s OSS/BSS team could “work out the distribution of loss from a small event to (be) a very big event” (for the telco’s brand value). Consider the loss of repute during sustained network outages. Consider the impact of negative word-of-mouth from billing mistakes. Consider how revenue leakage analysis and predictive network health management might offset losses.

Like this:

On Friday, we talked about how making compromises on OSS can actually be a method for reducing risk. We used the OSS vendor selection process to discuss the point, where many stakeholders contribute to the list of requirements that help to select the best-fit product for the organisation.

To continue with this same theme, I’d like to introduce you to a way of prioritising requirements that borrows from the risk / likelihood matrix commonly used in project management.

The diagram below shows the matrix as it applies to OSS.

The y-axis shows the frequency of use (of a particular feature / requirement). They x-axis shows the time / cost savings that will result from having this functionality or automation.

If you add two extra columns to your requirements list, the frequency of use and the resultant savings, you’ll quickly identify which requirements are highest priority (green) based on business benefit. Naturally there are other factors to consider, such as cost-benefit, but it should quickly narrow down to your 80/20 that will allow your OSS to make the most difference.

The same model can be used to sub-prioritise too. For example, you might have a requirement to activate orders – but some orders will occur very frequently, whilst other order types occur rarely. In this case, when configuring the order activation functionality, it might make sense to prioritise on the green order types first.

Like this:

If I start talking about doomsday scenarios where the global OSS job industry is decimated, most people will immediately jump to the conclusion that I’m predicting an artificial intelligence (AI) takeover. AI could have a role to play, but is not a key facet of the scenario I’m most worried about.

You’d think that OSS would be quite a niche industry, but there must be thousands of OSS practitioners in my home town of Melbourne alone. That’s partly due to large projects currently being run in Australia by major telcos such as nbn, Telstra, SingTel-Optus and Vodafone, not to mention all the smaller operators. Some of these projects are likely to scale back in coming months / years, meaning less seats in a game of OSS musical chairs. But this isn’t the doomsday scenario I’m hinting at in the title either. There will still be many roles at the telcos and the vendors / integrators that support them.

There are hundreds of OSS vendors in the market now, with no single dominant player. It’s a really fragmented market that would appear to be ripe for M&A (mergers and acquisitions). Ripe for consolidation, but massive consolidation is still not the doomsday scenario because there would still be many OSS roles in that situation.

The doomsday scenario I’m talking about is one where only one OSS gains domination globally. But how?

Most traditional telcos have a local geographic footprint with partners/subsidiaries in other parts of the world, but are constrained by the costs and regulations of a wired or cellular footprint to be able to reach all corners of the globe. All that uniqueness currently leads to the diversity of OSS offerings we see today. The doomsday scenario arises if one single network operator usurps all the traditional telcos and their legacy network / OSS / BSS stacks in one technological fell swoop.

How could a disruption of that magnitude happen? I’m not going to predict, but a satellite constellation such as the one proposed by Starlink has some of the hallmarks of such a scenario. By using low-earth orbit (LEO) satellites (ie lower latency than geostationary satellite solutions), point-to-point laser interconnects between them and peering / caching of data in the sky, it could fundamentally change the world of communications and OSS.

It has global reach, no need for carrier interconnect (hence no complex contract negotiations or OSS/BSS integration for that matter), no complicated lead-in negotiations or reinstatements, no long-haul terrestrial or submarine cable systems. None of the traditional factors that cost so much time and money to get customers connected and keep them connected (only the complication of getting and keeping the constellation of birds in the sky – but we’ll put that to the side for now). It would be hard for traditional telcos to compete.

I’m not suggesting that Starlink can or will be THE ubiquitous global communications network. What if Google, AWS or Microsoft added this sort of capability to their strengths in hosting / data? Such a model introduces a new, consistent network stack without the telcos’ tech debt burdens discussed here. The streamlined network model means the variant tree is millions of times simpler. And if the variant tree is that much simpler, so is the operations model and so is the OSS… with one distinct contradiction. It would need to scale for billions of customers rather than millions and trillions of events.

You might be wondering about all the enterprise OSS. Won’t they survive? Probably not. Comms networks are generally just an important means-to-an-end for enterprises. If the one global network provider were to service every organisation with local or global WANs, as well as all the hosting they would need, and hosted zero-touch network operations like Google is already pre-empting, would organisation have a need to build or own an on-premises OSS?

One ubiquitous global network, with a single pared back but hyperscaled OSS, most likely purpose-built with self-healing and/or AI as core constructs (not afterthoughts / retrofits like for existing OSS). How many OSS roles would survive that doomsday scenario?

Do you have an alternative OSS doomsday scenario that you’d like to share?

Hat tip again to Jay Fenton for pointing out what Starlink has been up to.

When we have a big OSS transformation to undertake, we tend to start with the use cases / requirements, work our way through the technical solution and build up an implementation plan before delivering it (yes, I’ve heavily reduced the real number of steps there!).

However, we sometimes overlook the organisational change management part. That’s the process of getting the customer’s organisation aligned to assist with the transformation, not to mention being fully skilled up to accept handover into operations. I’ve seen OSS projects that were nearly perfect technically, but ultimately doomed because the customer wasn’t ready to accept handover. Seasoned OSS veterans probably already have plans in place for handling organisational change through stakeholder management, training, testing, thorough handover-to-ops processes, etc. You can find some hints on the Free Stuff pages here on PAOSS.

In addition, long-time readers here on PAOSS have probably already seen a few posts about organisational management, but there’s a new gotcha that I’d like to add to the mix today – the changing operating model. This one is often overlooked. The changes made in a next-gen OSS can often have profound changes on the to-be organisation chart. Roles and responsibilities that used to be clearly defined now become blurred and obsoleted by the new solution.

This is particularly true for modern delivery models where cloud, virtualisation, as-a-service, etc change the dynamic. Demarcation points between IT, operations, networks, marketing, products, third-party suppliers, etc can need complete reconsideration. The most challenging part about understanding the re-mapping of operating models is that we often can’t even predict what they will be until we start using the new solution and refining our processes in-flight. We can start with a RACI and a bunch of “what if?” assumptions / scenarios to capture new operational mappings, but you can almost bet that it will need ongoing refinement.